Efficient Query Compilation in Replicated Databases

ABSTRACT

A secondary database system is configured to act as a backup system for a primary database system. The primary database system receives a query request from a client application in advance of receiving a query. Thereafter, the primary database system determines that a routing hint in the query request indicates that workload from the query may be shifted to the secondary database system. It can then be determined that execution of the query does not involve writing data. The primary database system then determines to instruct the client application to route the query to the secondary database system based on the routing hint. The primary database system then instructs the client application to route the query to the secondary database system. The query is then compiled and executed on the secondary database system such that a replica table does not replace the source table.

TECHNICAL FIELD

The subject matter described herein relates to database systems and more particularly to enhanced query compilation techniques for database systems employing a primary database and a secondary, hot-standby, database.

BACKGROUND

A database system includes a database and a database management system (DBMS). A database is an organized collection of data. A DBMS comprises computer software that executes on one or more processors and interacts with users, other applications, and a database to capture and analyze data. A DBMS may allow for the definition, creation, querying, update, and administration of databases.

SUMMARY

A computer system is provided that includes a primary database system and a secondary database system that is configured as a backup system for the primary database system. The secondary database system is capable of providing at least a minimum amount of essential functionality of the primary database system during a disruption to the primary database system. The primary database system receives a query request from a client application in advance of receiving a query. Thereafter, it is determined, by the primary database system, that a routing hint in the query request indicates that workload from the query may be shifted to the secondary database system. It can then be determined that execution of the query does not involve writing data. The primary database system then determines to instruct the client application to route the query to the secondary database system based on the routing hint. The primary database system then instructs the client application to route the query to the secondary database system. The query is then compiled on the secondary database system such that a replica table does not replace the source table. The compiled query is then executed on the secondary database system and responsive results can be provided.

The instructing of the client application to route the query to the secondary database system can include providing the identity of the secondary database system to the client application.

The query can be received from the client application requesting data retrieval at the secondary database system while in a hot-standby mode of operation.

It can be detected that the query is being compiled on the secondary database system which results in the query being compiled so that the replica table does not replace the source table. The detecting can be based on various factors such as a runtime context of the query.

One or more of the primary database system and the secondary database system is an in-memory database system.

Non-transitory computer program products (i.e., physically embodied computer program products) are also described that store instructions, which when executed by one or more data processors of one or more computing systems, cause at least one data processor to perform operations herein. Similarly, computer systems are also described that may include one or more data processors and memory coupled to the one or more data processors. The memory may temporarily or permanently store instructions that cause at least one processor to perform one or more of the operations described herein. In addition, methods can be implemented by one or more data processors either within a single computing system or distributed among two or more computing systems. Such computing systems can be connected and can exchange data and/or commands or other instructions or the like via one or more connections, including but not limited to a connection over a network (e.g., the Internet, a wireless wide area network, a local area network, a wide area network, a wired network, or the like), via a direct connection between one or more of the multiple computing systems, etc.

The subject matter described herein provides many technical advantages. As an example, the subject matter described herein provides more rapid and efficient query handling on a secondary database system by obviating the need for multiple query compilations.

The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the description below. Other features and advantages of the subject matter described herein will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a system diagram illustrating an example database system for use in connection with the current subject matter.

FIG. 2 is a system diagram illustrating an example database system that can support distribution of server components across multiple hosts for scalability and/or availability purposes for use in connection with the current subject matter.

FIG. 3 is a diagram illustrating an architecture for an index server for use in connection with the current subject matter.

FIG. 4 is a functional flow diagram illustrating an architecture to support load balancing between a primary database system and a secondary database system, which serves as hot-standby to the primary database system, for use in connection with the current subject matter.

FIG. 5 depicts one example solution to managing load balancing in a HA/DR system.

FIG. 6 depicts another example solution to managing load balancing in a HA/DR system.

FIG. 7 depicts a flow diagram in which a query routed to a secondary database system is compiled twice on a secondary database system; and

FIG. 8 depicts a flow diagram in which a query routed to a secondary database system is only compiled once on the secondary database system.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

The subject matter described herein is directed to secondary, backup database systems to execute queries to reduce the workload of a primary database system and the more efficient handling of queries on such secondary, backup database system. In some examples, systems and methods disclosed herein utilize a hint in a query request from an application to identify a query that may be candidate for execution by a secondary database system and the avoidance of unnecessary query compilation on the secondary database system.

FIG. 1 is a diagram 100 illustrating a database system 105 that can be used to implement aspects of the current subject matter. The database system 105 can, for example, be an in-memory database in which all relevant data is kept in main memory so that read operations can be executed without disk I/O and in which disk storage is required to make any changes durable. The database system 105 can include a plurality of servers including, for example, one or more of an index server 110, a name server 115, and/or an application server 120. The database system 105 can also include one or more of an extended store server 125, a database deployment infrastructure (DDI) server 130, a data provisioning server 135, and/or a streaming cluster 140. The database system 105 can be accessed by a plurality of remote clients 145, 150 via different protocols such as SQL/MDX (by way of the index server 110) and/or web-based protocols such as HTTP (by way of the application server 120).

The index server 110 can contain in-memory data stores and engines for processing data. The index server 110 can also be accessed by remote tools (via, for example, SQL queries), that can provide various development environment and administration tools. Additional details regarding an example implementation of the index server 110 is described and illustrated in connection with diagram 300 of FIG. 3.

The name server 115 can own information about the topology of the database system 105. In a distributed database system, the name server 115 can know where various components are running and which data is located on which server. In a database system 105 with multiple database containers, the name server 115 can have information about existing database containers, and it can also host the system database. For example, the name server 115 can manage the information about existing tenant databases. Unlike a name server 115 in a single-container system, the name server 115 in a database system 105 having multiple database containers does not store topology information such as the location of tables in a distributed database. In a multi-container database system 105 such database-level topology information can be stored as part of the catalogs of the tenant databases.

The application server 120 can enable native web applications used by one or more remote clients 150 accessing the database system 105 via a web protocol such as HTTP. The application server 120 can allow developers to write and run various database applications without the need to run an additional application server. The application server 120 can also be used to run web-based tools 155 for administration, life-cycle management and development. Other administration and development tools 160 can directly access the index server 110 for, example, via SQL and other protocols.

The extended store server 125 can be part of a dynamic tiering option that can include a high-performance disk-based column store for very big data up to the petabyte range and beyond. Less frequently accessed data (for which is it non-optimal to maintain in main memory of the index server 110) can be put into the extended store server 125. The dynamic tiering of the extended store server 125 allows for hosting of very large databases with a reduced cost of ownership as compared to conventional arrangements.

The DDI server 130 can be a separate server process that is part of a database deployment infrastructure (DDI). The DDI can be a layer of the database system 105 that simplifies the deployment of database objects using declarative design time artifacts. DDI can ensure a consistent deployment, for example by guaranteeing that multiple objects are deployed in the right sequence based on dependencies, and by implementing a transactional all-or-nothing deployment.

The data provisioning server 135 can provide enterprise information management and enable capabilities such as data provisioning in real time and batch mode, real-time data transformations, data quality functions, adapters for various types of remote sources, and an adapter SDK for developing additional adapters.

The streaming cluster 140 allows for various types of data streams (i.e., data feeds, etc.) to be utilized by the database system 105. The streaming cluster 140 allows for both consumption of data streams and for complex event processing.

FIG. 2 is a diagram 200 illustrating a variation of the database system 105 that can support distribution of server components across multiple hosts for scalability and/or availability purposes. This database system 105 can, for example, be identified by a single system ID (SID) and it is perceived as one unit from the perspective of an administrator, who can install, update, start up, shut down, or backup the system as a whole. The different components of the database system 105 can share the same metadata, and requests from client applications 230 can be transparently dispatched to different servers 110 ₁₋₃, 120 ₁₋₃, in the system, if required.

As is illustrated in FIG. 2, the distributed database system 105 can be installed on more than one host 210 ₁₋₃. Each host 210 ₁₋₃ is a machine that can comprise at least one data processor (e.g., a CPU, etc.), memory, storage, a network interface, and an operation system and which executes part of the database system 105. Each host 210 ₁₋₃ can execute a database instance 220 ₁₋₃ which comprises the set of components of the distributed database system 105 that are installed on one host 210 ₁₋₃. FIG. 2 shows a distributed system with three hosts, which each run a name server 110 ₁₋₃, index server 120 ₁₋₃, and so on (other components are omitted to simplify the illustration).

FIG. 3 is a diagram 300 illustrating an architecture for the index server 110 (which can, as indicated above, be one of many instances). A connection and session management component 302 can create and manage sessions and connections for the client applications 145. For each session, a set of parameters can be maintained such as, for example, session variables, auto commit settings or the current transaction isolation level.

Requests from the client applications 145 can be processed and executed by way of a request processing and execution control component 310. The database system 105 offers rich programming capabilities for running application-specific calculations inside the database system. In addition to SQL, MDX, and WIPE, the database system 105 can provide different programming languages for different use cases. SQLScript can be used to write database procedures and user defined functions that can be used in SQL statements. The L language is an imperative language, which can be used to implement operator logic that can be called by SQLScript procedures and for writing user-defined functions.

Once a session is established, client applications 145 typically use SQL statements to communicate with the index server 110 which can be handled by a SQL processor 312 within the request processing and execution control component 310. Analytical applications can use the multidimensional query language MDX (MultiDimensional eXpressions) via an MDX processor 322. For graph data, applications can use GEM (Graph Query and Manipulation) via a GEM processor 316, a graph query and manipulation language. SQL statements and MDX queries can be sent over the same connection with the client application 145 using the same network communication protocol. GEM statements can be sent using a built-in SQL system procedure.

The index server 110 can include an authentication component 304 that can be invoked when a new connection with a client application 145 is established. Users can be authenticated either by the database system 105 itself (login with user and password) or authentication can be delegated to an external authentication provider. An authorization manager 306 can be invoked by other components of the database system 105 to check whether the user has the required privileges to execute the requested operations.

Each statement can be processed in the context of a transaction. New sessions can be implicitly assigned to a new transaction. The index server 110 can include a transaction manager 344 that coordinates transactions, controls transactional isolation, and keeps track of running and closed transactions. When a transaction is committed or rolled back, the transaction manager 344 can inform the involved engines about this event so they can execute necessary actions. The transaction manager 344 can provide various types of concurrency control and it can cooperate with a persistence layer 346 to achieve atomic and durable transactions.

Incoming SQL requests from the client applications 145 can be received by the SQL processor 312. Data manipulation statements can be executed by the SQL processor 312 itself. Other types of requests can be delegated to the respective components. Data definition statements can be dispatched to a metadata manager 308, transaction control statements can be forwarded to the transaction manager 344, planning commands can be routed to a planning engine 318, and task related commands can forwarded to a task manager 324 (which can be part of a larger task framework) Incoming MDX requests can be delegated to the MDX processor 322. Procedure calls can be forwarded to the procedure processor 314, which further dispatches the calls, for example to a calculation engine 326, the GEM processor 316, a repository 330, or a DDI proxy 328.

The index server 110 can also include a planning engine 318 that allows planning applications, for instance for financial planning, to execute basic planning operations in the database layer. One such basic operation is to create a new version of a data set as a copy of an existing one while applying filters and transformations. For example, planning data for a new year can be created as a copy of the data from the previous year. Another example for a planning operation is the disaggregation operation that distributes target values from higher to lower aggregation levels based on a distribution function.

The SQL processor 312 can include an enterprise performance management (EPM) runtime component 320 that can form part of a larger platform providing an infrastructure for developing and running enterprise performance management applications on the database system 105. While the planning engine 318 can provide basic planning operations, the EPM platform provides a foundation for complete planning applications, based on by application-specific planning models managed in the database system 105.

The calculation engine 326 can provide a common infrastructure that implements various features such as SQLScript, MDX, GEM, tasks, and planning operations. The SQL processor 312, the MDX processor 322, the planning engine 318, the task manager 324, and the GEM processor 316 can translate the different programming languages, query languages, and models into a common representation that is optimized and executed by the calculation engine 326. The calculation engine 326 can implement those features using temporary results 340 which can be based, in part, on data within the relational stores 332.

Metadata can be accessed via the metadata manager component 308. Metadata, in this context, can comprise a variety of objects, such as definitions of relational tables, columns, views, indexes and procedures. Metadata of all these types can be stored in one common database catalog for all stores. The database catalog can be stored in tables in a row store 336 forming part of a group of relational stores 332. Other aspects of the database system 105 including, for example, support and multi-version concurrency control can also be used for metadata management. In distributed systems, central metadata is shared across servers and the metadata manager 308 can coordinate or otherwise manage such sharing.

The relational stores 332 form the different data management components of the index server 110 and these relational stores can, for example, store data in main memory. The row store 336, a column store 338, and a federation component 334 are all relational data stores which can provide access to data organized in relational tables. The column store 338 can stores relational tables column-wise (i.e., in a column-oriented fashion, etc.). The column store 338 can also comprise text search and analysis capabilities, support for spatial data, and operators and storage for graph-structured data. With regard to graph-structured data, from an application viewpoint, the column store 338 could be viewed as a non-relational and schema-flexible in-memory data store for graph-structured data. However, technically such a graph store is not a separate physical data store. Instead it is built using the column store 338, which can have a dedicated graph API.

The row store 336 can stores relational tables row-wise. When a table is created, the creator can specify whether it should be row or column-based. Tables can be migrated between the two storage formats. While certain SQL extensions are only available for one kind of table (such as the “merge” command for column tables), standard SQL can be used on all tables. The index server 110 also provides functionality to combine both kinds of tables in one statement (join, sub query, union).

The federation component 334 can be viewed as a virtual relational data store. The federation component 334 can provide access to remote data in external data source system(s) 354 through virtual tables, which can be used in SQL queries in a fashion similar to normal tables.

The database system 105 can include an integration of a non-relational data store 342 into the index server 110. For example, the non-relational data store 342 can have data represented as networks of C++ objects, which can be persisted to disk. The non-relational data store 342 can be used, for example, for optimization and planning tasks that operate on large networks of data objects, for example in supply chain management. Unlike the row store 336 and the column store 338, the non-relational data store 342 does not use relational tables; rather, objects can be directly stored in containers provided by the persistence layer 346. Fixed size entry containers can be used to store objects of one class. Persisted objects can be loaded via their persisted object IDs, which can also be used to persist references between objects. In addition, access via in-memory indexes is supported. In that case, the objects need to contain search keys. The in-memory search index is created on first access. The non-relational data store 342 can be integrated with the transaction manager 344 to extends transaction management with sub-transactions, and to also provide a different locking protocol and implementation of multi version concurrency control.

An extended store is another relational store that can be used or otherwise form part of the database system 105. The extended store can, for example, be a disk-based column store optimized for managing very big tables, which one may not want to keep in memory (as with the relational stores 332). The extended store can run in an extended store server 125 separate from the index server 110. The index server 110 can use the federation component 334 to send SQL statements to the extended store server 125.

The persistence layer 346 is responsible for durability and atomicity of transactions. The persistence layer 346 can ensure that the database system 105 is restored to the most recent committed state after a restart and that transactions are either completely executed or completely undone. To achieve this goal in an efficient way, the persistence layer 346 can use a combination of write-ahead logs, shadow paging and savepoints. The persistence layer 346 can provide interfaces for writing and reading persisted data and it can also contain a logger component that manages a transaction log. Transaction log entries can be written explicitly by using a log interface or implicitly when using the virtual file abstraction.

The persistence layer 236 stores data in persistent disk storage 348 which, in turn, can include data volumes 350 and/or transaction log volumes 352 that can be organized in pages. Different page sizes can be supported, for example, between 4k and 16M. Data can be loaded from the disk storage 348 and stored to disk page wise. For read and write access, pages can be loaded into a page buffer in memory. The page buffer need not have a minimum or maximum size, rather, all free memory not used for other things can be used for the page buffer. If the memory is needed elsewhere, least recently used pages can be removed from the cache. If a modified page is chosen to be removed, the page first needs to be persisted to disk storage 348. While the pages and the page buffer are managed by the persistence layer 346, the in-memory stores (i.e., the relational stores 332) can access data within loaded pages.

In many applications, data systems may be required to support operations on a 24/7 schedule, and data system providers may be required to guarantee a maximum amount of downtime, that is time during which a system is not able to fully support ongoing operations. When a system is required to ensure an agreed level of operational performance, it may be referred to as a high availability system (“HA”). One solution to guarantee substantially continuous uptime with no, or very little, downtime is to maintain one or more hot-standby systems. A hot-standby system, or a backup system, is a system that may be activated quickly in the event of a disruption causing one or more functions of a primary operational data system to fail. Such a disruption may be referred to as a disaster, and the process of restoring a data system to full operations may be referred to as disaster-recovery (“DR”).

A hot-standby system may be an exact replica of a primary operational system that is capable of providing all the functions provided by the primary operational system, or a hot-standby may be a system that is capable of providing a minimum amount of essential functionality during the time required to restore the primary operational data system. The time it takes after a disaster to restore full, or minimum, functionality of a data system, for example by bringing a hot-standby online, is referred to as recovery time. In an effort to minimize recovery time, and thereby downtime, a hot-standby system is typically in a state just short of fully operational. For example, a system architecture may be implemented in which all functional systems of the hot-standby are active and operational, and all system and data changes or updates occur in the primary operational system and the hot-standby at the exact same time. In such a case the only difference in the two systems may be that the primary is configured to respond to user requests and the hot-standby system is not. In other hot-standby systems one or more functions may be disabled until mission critical systems of the hot-standby are observed to be operating normally, at which time the remaining functions may be brought online.

In many applications, data systems may be required to provide prompt responses to users and applications that rely on the data managed by the data system. Providers and designers of data systems may be required to guarantee a minimum average throughput over time, or an average maximum response time. The speed with which a data system responds to a request from a user or an application may be dependent on many factors, but all systems are limited in the number of requests they can handle in a given period of time. When a data system manages a relatively large amount of data, and supports a relatively large number of users or applications, during high workloads a request may be queued, buffered or rejected until sufficient system resources are available to complete the request. When this happens, average throughput goes down and average response time goes up. One solution to such a problem is to distribute the workload across multiple processing systems. This is known as load balancing.

One drawback to load balancing in HA systems is that load balancing may require additional processing systems, which in turn have a high cost. It is often the case with certain data systems supporting critical functions of an organization that additional systems are needed to perform both load balancing and HA functionality to efficiently support continuous operations. Given the redundant nature of DR systems, hot-standby systems are often left undisturbed unless a disaster occurs. Thus, in some circumstances, it is desirable to implement and maintain a combination high availability/disaster recovery (HA/DR) system with load balancing that includes both a primary operational system and a hot-standby system, and potentially one or more tertiary systems. Such a combination system allows for load balancing of workload between the processing systems of both the primary operational system and the hot-standby system, without disrupting the ability of the hot-standby system to assume primary functionality in the event of a disaster.

FIG. 4 is a functional flow diagram illustrating an architecture 400 to support load balancing between a primary database system, or primary system 405 a and a secondary database system, or secondary system 405 b, which serves as hot-standby to primary system 405 a. Each of the primary system 405 a and the secondary system 405 b may be a single instance system, similar to database system 105 depicted in FIG. 1, or each may be a distributed variation of database system 105 as depicted in FIG. 2. Such an architecture 400 may be useful in a high availability data system, or in a disaster recovery system, or in a combination HA/DR system.

Each of the primary system 405 a and secondary system 405 b may include a load balancing functionality. Such load balancing functionality may for example be contained within a distinct load balancing server 470 a or 470 b. But, such load balancing functionality may be managed by any suitable processing system. For example, the application server 120 of the primary system may also manage the load balancing of requests issued to the application server of the primary system 405 a, sending requests to the secondary system 405 b as necessary to maintain a well distributed workload.

As depicted in FIG. 4, each of the primary system 405 a and the secondary system 405 b includes a load balancing server 470 a and 470 b which respectively receive requests from user applications directed to the primary system 405 a or the secondary system 405 b. Such request may come from either admin tools 460 or web-based tools 450, or any other user application. Upon receiving a request a load balancing server, e.g. 470 a, determines how to distribute the workload. As depicted load balancing server 470 a routes an SQL request 465 from admin tools 460 to the index server 110 of the primary system 405 a, while routing an HTTP request 455 from web-based tools 450 to the application server 120 of the secondary system 405 b.

Load balancing of resources between a primary system 405 a and a secondary system 405 b can give rise to a number of complicating issues. For example, if either of the requests 455, 465 requires writing to one or more data tables, or modifying a data table, then the two systems 405 a, 405 b will diverge. After many instances of write requests being distributed between the primary system 405 a and the secondary system 405 b, the two systems would be substantially different, and likely unusable. In another example, an application request, e.g. 465, may perform a write transaction that is followed by a read transaction, e.g. 455, related to the data written by the write request 465. If the write request is allocated to the primary system 405 a, the read request would obtain a different result depending on whether the subsequent read transaction is carried out by the primary system 405 a or by the secondary system 405 b.

Load balancing in a HA/DR system, by distributing a portion of the workload of a primary data system to a hot-standby or backup system must be done in a way that does not disturb the principal purpose of the backup system, which is to substantially eliminate downtime in a high availability system by enabling quick and efficient recovery of operations. In other words, as a rule, load balancing cannot break the hot-standby. Given this principal purpose, any solution that enables load balancing of workload between a primary system and a backup system must maintain the backup system in an identical, or nearly identical, state as the primary system. Such a solution should also avoid or prohibit any actions which may cause the state of the backup system to substantially diverge from the state of the primary system. In this way, in the event of a partial or total failure of the primary system due to disaster, the backup system can failover to a primary system mode with minimal or no impact to client applications.

FIG. 5 depicts one example solution to managing load balancing in a HA/DR system 500. HA/DR system 500 includes a primary system 505 and a secondary system 510 and is capable of load balancing between primary system 505 and secondary system 510 without interfering with the hot-standby functionality of the secondary system 510. Each of primary system 505 and secondary system 510 may be single instance database systems similar to database system 105 depicted in FIG. 1, or a distributed variation of database system 105 as depicted in FIG. 2. Furthermore, each of primary system 505 and secondary system 510 may comprise less, more or all the functionality ascribed to index server 110, 300, name server 115, application server 120, extended store server 125, DDI server 130, data provisioning server 135, and stream cluster 140. But, for simplicity of illustration HA/DR system 500 has been simplified to highlight certain functionality by merely distinguishing between processing control 555, 560 and a persistence layer 565, 570 of each respective system 505, 510.

A collection of clients may each maintain an open connection to both the primary system 505 and the secondary system 525. For example, client 515 maintains a read/write connection 520 to the primary system 505 and a read only connection 525 to the secondary system 510. Alternatively, client 515 may maintain a read/write connection with each of the primary system 505 and the secondary system 510, while processes within the secondary system 510 itself prohibit execution of any requests that require a write transaction upon the secondary system while it is in backup mode. Management of load balancing of the workload required by a client application executing at client 515 may be managed by the client 515 application itself. Alternatively, a client 515 application may submit a query request to the primary system 505. A process control 555 load balancing process executing on processor 545 then may determine where the query should be executed and replies to the client 515 with instructions identifying which system the client 515 should issue the query to.

Primary system 505 may include an in-memory database in which substantially all actively used data may be kept and maintained in main memory 535 so that operations can be executed without disk I/O, which requires accessing disk storage. Active operations of applications within processing control 555 may cause processor 545 to read and write data into main memory 535 or to disk in the persistence layer 565. Processing control 555 applications also cause processor 545 to generate transaction logs for capturing data transactions upon the database, which processor 545 then persists in the log volumes 585. As substantially all actively used data may reside in-memory, processing control 555 may interact primarily with data held in main memory while only resorting to data volumes 575 for retrieving and writing less often used data. Additional processes within processing control 555 may be executed by processor 545 to ensure that in-memory data is persisted in persistence layer 565, so that the data is available upon restart or recovery.

Primary system 505 may be the primary operational system for providing the various functionality necessary to support 24/7 operations for an organization. Secondary system 510 may be a hot-standby, ready to come online with minimal recovery time so as to minimize downtime. Secondary system 510 may be an identical physical system as primary system 505, and may be configured in a substantially identical manner in order to enable the secondary system 510 to provide all the same functionality as primary system 505. For example, processing control 560 may include all the same applications and functionality as processing control 555, and persistence layer 570 may include data volumes 580 and log volumes 590 that are configured in an identical manner as data volumes 575 and log volumes 585 respectively. Secondary system 510 may also include an in-memory database kept and maintained primarily in main memory 540.

Primary system 505 and secondary system 510 differ in that all requests, from client 515 or otherwise, that require a write transaction are executed only in primary system 505. Primary system 505 and secondary system 510 further differ in that all write transactions to persistent objects are prohibited by the secondary system 510. In order to propagate changes to the data or the underlying schema from the primary system 505 to the secondary system 510, processor 545 also replicates 530 transaction logs directly to the process control 560 of the secondary system 510. Process control 560 includes one or more applications that cause processor 550 to then replay the transaction logs replicated from the primary system 505, thereby replaying the transactions at the secondary system 510. As transaction logs are replayed, the various transactions executed at the primary system become reflected in the secondary system 510. In order to ensure both the HA functionality and the load balancing functionality, replay of the transaction logs at the secondary system places data in main memory 540, and also persists any data committed in the primary system to persistence layer 570 to be stored by data volumes 580. Replay of the transaction logs at the secondary system 510 may also results in the transaction logs being persisted in log volumes 590.

Transaction logs may be replicated in different ways. Where maintaining a standby system in as close to the same state as the primary system is an important factor, logs may be replicated synchronously meaning that the primary system will not commit a transaction until the secondary successfully responds to the log replication. One appreciates that this will slow performance of the primary system. Conversely, where performance of a primary system is a priority, logs may be replicated asynchronously, in which case the primary operation proceeds with committing transactions without waiting for a response. Various tradeoffs can be made between these two scenarios to achieve a proper level of performance while ensuring replication of critical data.

It will be appreciated from the detailed description above that such a secondary system in standby mode, such as secondary system 510, can only be as current as its most recently replayed transaction logs. Transaction logs are replicated and replayed at the secondary system 510 only after a transaction executes in the primary system 505. Secondary system 510, therefore, is always slightly behind an associated primary system 515. Also, there is no guarantee that a query routed to the primary system in a load balancing effort will be executed before, during or after a particular transaction log is replayed. Thus, the state of the primary system 505 and the state of the secondary system will rarely if ever be identical. But, by addressing certain concerns, secondary system 510 may be kept in a state substantially close to the same state as the primary system 505 such that the workload required by many operations can be supported by the secondary 510. These are just a few of the issues to be addressed in order to provide a robust load balancing implementation in a HA/DR architecture, where the hot-standby system also functions to carry a portion of the workload. One or more solutions to issues arising by the load balancing solution depicted in FIG. 5 are now addressed.

FIG. 6 depicts another example solution to managing load balancing in a HA/DR system 600. HA/DR system 600 includes a primary database system 605, a secondary database system 610, and a communication channel 655 for propagating transaction logs and changes to data or the underlying schema from the primary system 605 to the secondary system 610. The HA/DR system 600 is capable of load balancing between primary system 605 and secondary system 610 without interfering with the hot-standby functionality of the secondary system 610. Each of primary system 605 and secondary system 610 may be single instance database systems similar to database system 105 depicted in FIG. 1, or a distributed variation of database system 105 as depicted in FIG. 2. Furthermore, each of primary system 605 and secondary system 610 may comprise less, more or all the functionality ascribed to primary system 505 and secondary system 510, index server 110, 300, name server 115, application server 120, extended store server 125, DDI server 130, data provisioning server 135, and stream cluster 140. But, for simplicity of illustration HA/DR system 600 has been simplified to highlight certain functionality by merely distinguishing between index server 615, 620 and a session service 625, 630 of each respective system 605, 610. Also, each of index server 615, 620 may comprise less, more or all the functionality ascribed to index server 110, 300 and each of session service 625, 630 may comprise less, more or all the functionality ascribed to connection and session management component 302.

A client application 634 may invoke one or more client libraries 635 to establish connections with the primary and secondary server systems 605, 610. As a result, one or more client libraries 635 may each maintain an open connection to both the primary system 605 and the secondary system 610. For example, client library 635 may maintain a read/write connection 645 to the primary system 605 and a read only connection 650 to the secondary system 610. Alternatively, client library 635 may maintain a read/write connection with each of the primary system 605 and the secondary system 610, while processes within the secondary system 610 itself prohibit execution of any requests that require a write transaction upon the secondary system while it is in backup mode.

Management of load balancing of the workload required by a client application 634, in this example, is managed by both the client library 635 and the primary system 605. The client library 635 may submit a query request to the session service 625 in the index server 615 of the primary system 605. The client application 634 may indicate in the query request through a hint that it is acceptable (or preferable) to the client application 634 to have the query executed at the secondary system 610. A load balancing process executing on a processor within the index server 615 in the primary system 605 then may determine where the query should be executed and replies to the client 615 with instructions identifying the system to which the client 615 should issue the query. In this example, the index server 615 determines that the query should be executed at the secondary system 610 and instructs the client library 635 to issue the query to the secondary system 610. The hint may indicate to the primary system 605 the preference of the client library 635 for the query to execute at the secondary system if possible.

With the architecture of FIG. 6, a replication option can be provided referred to as database system replication (DSR) which can serve to increase high availability. This arrangement focuses on addressing datacenter outages by replicating entire database contents across data centers, and by providing Active/Active (Read Enabled) features of DSR to allow selective usage of the secondary system 610 for read purposes.

The architecture of FIG. 6, can, in some implementations, provide an additional or alternative replication option referred to herein as asynchronous table replication (ATR) which focuses on load balancing between the primary system 605 and the secondary system 610 and, additionally, scalable read performance by replicating a selected list of tables within a single data center.

DSR and ATR can be used together in a query of a system as in FIG. 5 (e.g., an Active/Active (Read Enabled) system) such as provided below:

--Create table T1 on master indexserver create column table T1(a int, b int) at ‘xiy150840964a:30103’; --A replica table of T1 named _SYS_REP_t1#0 is created on a slave indexserver alter table T1 add asynchronous replica at ‘xiy150840964a:30140’; --Enable replica table _SYS_REP_T1#0 ALTER TABLE T1 ENABLE ASYNCHRONOUS REPLICA; --Define a query hint using HSR and ATR ALTER SYSTEM ALTER CONFIGURATION (‘indexserver.ini’, ‘system’) SET (‘hint_result_lag_hana_short’, ‘enable_features’) = ‘sr,atr’ WITH RECONFIGURE; --Execute a query with hint based routing SELECT * FROM T1 WITH HINT(RESULT_LAG(‘hana_short’));

Whether DSR or ATR is chosen can depend on the preference order defined in the hint. With the above example, DSR is specified as being ahead of ATR, then the query is processed as provided in diagram 700 of FIG. 7. Initially, at 710, a query received from a client is compiled on a primary database system (e.g., primary system 605). Compilation in this regard can include the generation of a query plan having code segments which specifies which tables and corresponding field names are subject to the operations specified in the query. One of these tables can include a source table on the primary database system. Thereafter, at 720, it is determined whether the query comprises a hint to route the query to a secondary database system (e.g., secondary system 610). If there is no hint, at 730, the query is executed on the primary system and results are provided back to the requesting client.

If the query contains a hint to route the query to the secondary system, then, at 740, the query is compiled on the secondary system. In this scenario, a replica table on the secondary system replaces the source table. With the example above, during compilation on the secondary system, the ATR takes effect and the replica table _SYS_REP_T1#0 replaces source table ‘T1’ in the generated query plan.

However, in this situation, at 750, the query falls back from the replicable table to the source table due to the replica table being disabled or otherwise unavailable on the secondary system. The replica table can, in some variations, be disabled by default, as the secondary database system is configured as a hot-standby system for the primary database system that is capable of providing at least a minimum amount of essential functionality of the primary database system during a disruption to the primary database system. Stated differently, due to the replica table on the secondary system being disabled, the generated query plan is considered as invalid and the query has to fallback form replica table _SYS_REP_T1#0 to source table T1.

The query fallback requires, at 760, the query to be compiled again on the secondary table without replacing the source table. Thereafter, at 770, the compiled query is executed on the secondary system and the results are provided to the requesting client. As will be appreciated, the scenario outlined in FIG. 7 is inefficient in that it requires three different compilations of the query (one on the primary system and two on the secondary system). In addition to unnecessarily consuming computing resources, the multiple compilation slows down query execution times.

FIG. 8 is a diagram 800 illustrating an enhanced approach in which only the query is only compiled once on the secondary system. Initially, at 810, a query received from a client is compiled on a primary database system (e.g., primary system 605). Compilation in this regard can include the generation of a query plan having code segments which specifies which tables and corresponding field names are subject to the operations specified in the query. One of these tables can include a source table on the primary database system. Thereafter, at 820, it is determined whether the query comprises a hint to route the query to a secondary database system (e.g., secondary system 610). If there is no hint, at 830, the query is executed on the primary system and results are provided back to the requesting client.

If the query contains a hint to route the query to the secondary system, then, at 840, the query is compiled on the secondary system. In this scenario, it is detected (e.g., from runtime context) that the query is being compiled on a secondary system, and as such, table replacement (i.e., replacing a source table with a replica table) is bypassed during query compilation.

One or more aspects or features of the subject matter described herein can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) computer hardware, firmware, software, and/or combinations thereof. These various aspects or features can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

These computer programs, which can also be referred to as programs, software, software applications, applications, components, or code, include machine instructions for a programmable processor, and can be implemented in a high-level procedural language, an object-oriented programming language, a functional programming language, a logical programming language, and/or in assembly/machine language. As used herein, the term “machine-readable medium” refers to any computer program product, apparatus and/or device, such as for example magnetic discs, optical disks, memory, and Programmable Logic Devices (PLDs), used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor. The machine-readable medium can store such machine instructions non-transitorily, such as for example as would a non-transient solid-state memory or a magnetic hard drive or any equivalent storage medium. The machine-readable medium can alternatively or additionally store such machine instructions in a transient manner, such as for example as would a processor cache or other random access memory associated with one or more physical processor cores.

To provide for interaction with a user, the subject matter described herein may be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) and/or a touch screen by which the user may provide input to the computer. Other kinds of devices may be used to provide for interaction with a user as well; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

In the descriptions above and in the claims, phrases such as “at least one of” or “one or more of” may occur followed by a conjunctive list of elements or features. The term “and/or” may also occur in a list of two or more elements or features. Unless otherwise implicitly or explicitly contradicted by the context in which it is used, such a phrase is intended to mean any of the listed elements or features individually or any of the recited elements or features in combination with any of the other recited elements or features. For example, the phrases “at least one of A and B;” “one or more of A and B;” and “A and/or B” are each intended to mean “A alone, B alone, or A and B together.” A similar interpretation is also intended for lists including three or more items. For example, the phrases “at least one of A, B, and C;” “one or more of A, B, and C;” and “A, B, and/or C” are each intended to mean “A alone, B alone, C alone, A and B together, A and C together, B and C together, or A and B and C together.” In addition, use of the term “based on,” above and in the claims is intended to mean, “based at least in part on,” such that an unrecited feature or element is also permissible.

The subject matter described herein can be embodied in systems, apparatus, methods, and/or articles depending on the desired configuration. The implementations set forth in the foregoing description do not represent all implementations consistent with the subject matter described herein. Instead, they are merely some examples consistent with aspects related to the described subject matter. Although a few variations have been described in detail above, other modifications or additions are possible. In particular, further features and/or variations can be provided in addition to those set forth herein. For example, the implementations described above can be directed to various combinations and subcombinations of the disclosed features and/or combinations and subcombinations of several further features disclosed above. In addition, the logic flows depicted in the accompanying figures and/or described herein do not necessarily require the particular order shown, or sequential order, to achieve desirable results. Other implementations may be within the scope of the following claims. 

What is claimed is:
 1. A computer system comprising: one or more processors; a primary database system implemented by the one or more processors; and a secondary database system implemented by the one or more processors, the secondary database system configured as a hot-standby system for the primary database system that is capable of providing at least a minimum amount of essential functionality of the primary database system during a disruption to the primary database system; wherein the primary database system is configured by programming instructions, executable on the computer system, to cause the one or more processors to: determine from a query request from a client application directed to the primary database system that workload from a query may be shifted to the secondary database system; determine that a routing hint in the query request indicates that workload from the query may be shifted to the secondary database system; instruct, based on the routing hint, the client application to direct the secondary database system to execute the query; compile the query on the secondary database system such that a replica table does not replace the source table; execute the compiled query on the secondary database system; and provide results responsive to executed compiled query.
 2. The computer system according to claim 1, wherein the programming instructions to cause the one or more processors to instruct the client application to direct the secondary database system to execute the query comprises programming instructions to cause the one or more processors to provide the identity of the second database system to the client application.
 3. The computer system according to claim 1, wherein the programming instructions to cause the one or more processors to instruct the client application to direct the secondary database system to execute the query comprises programming instructions to cause the one or more processors to receive the query from the client application requesting data retrieval at the secondary database system while in a hot-standby mode of operation.
 4. The computer system according to claim 1, wherein the programming instructions to cause the one or more processors to instruct the client application to direct the secondary database system to execute the query comprises programming instructions to cause the one or more processors to detect that the query is being compiled on the secondary database system which results in the query being compiled so that the replica table does not replace the source table.
 5. The computer system according to claim 1, wherein the detecting is based on a runtime context of the query.
 6. The computer system according to claim 1, wherein the primary database system is an in-memory database system.
 7. The computer system according to claim 6, wherein the secondary database system is an in-memory database system.
 8. A computer-implemented method in a computer system comprising a primary database system and a secondary database system, the secondary database system configured as a backup system for the primary database system that is capable of providing at least a minimum amount of essential functionality of the primary database system during a disruption to the primary database system, the method comprising: receiving by the primary database system a query request from a client application in advance of receiving a query, determining by the primary database system that a routing hint in the query request indicates that workload from the query may be shifted to the secondary database system; determining that execution of the query does not involve writing data; determining by the primary database system to instruct the client application to route the query to the secondary database system based on the routing hint; instructing, by the primary database system, the client application to route the query to the secondary database system; compiling the query on the secondary database system such that a replica table does not replace the source table; executing the compiled query on the secondary database system; and providing results responsive to executed compiled query
 9. The method according to claim 8, wherein instructing the client application to route the query to the secondary database system comprises providing the identity of the secondary database system to the client application.
 10. The method according to claim 8, further comprising: receiving the query from the client application requesting data retrieval at the secondary database system while in a hot-standby mode of operation.
 11. The method according to claim 8, further comprising: detecting that the query is being compiled on the secondary database system which results in the query being compiled so that the replica table does not replace the source table.
 12. The method according to claim 8, wherein the detecting is based on a runtime context of the query.
 13. The method according to claim 8, wherein the primary database system is an in-memory database system.
 14. The method according to claim 13, wherein the secondary database system is an in-memory database system.
 15. A non-transitory computer readable storage medium embodying programming instruction for performing a method, the method comprising: receiving by a primary database system a query request from a client application in advance of receiving a query, determining by the primary database system that a routing hint in the query request indicates that workload from the query may be shifted to a secondary database system, the secondary database system configured as a backup system for the primary database system that is capable of providing at least a minimum amount of essential functionality of the primary database system during a disruption to the primary database system; determining that execution of the query does not involve writing data; determining by the primary database system to instruct the client application to route the query to the secondary database system based on the routing hint; instructing, by the primary database system, the client application to route the query to the secondary database system; compiling the query on the secondary database system such that a replica table does not replace the source table; executing the compiled query on the secondary database system; and providing results responsive to executed compiled query.
 16. The non-transitory computer readable storage medium according to claim 15, wherein instructing the client application to route the query to the secondary database system comprises providing the identity of the secondary database system to the client application.
 17. The non-transitory computer readable storage medium according to claim 15, wherein the method further comprises: receiving the query from the client application requesting data retrieval at the secondary database system while in a hot-standby mode of operation.
 18. The non-transitory computer readable storage medium according to claim 17, wherein the method further comprises: detecting that the query is being compiled on the secondary database system which results in the query being compiled so that the replica table does not replace the source table.
 19. The non-transitory computer readable storage medium according to claim 18, wherein the detecting is based on a runtime context of the query.
 20. The non-transitory computer readable storage medium according to claim 19, wherein the primary database system is an in-memory database system and the secondary database system is an in-memory database system. 